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  • 标题:Bank Valuation Research: Experience of the Baltic States
  • 本地全文:下载
  • 作者:Marius Strumickas ; Loreta Valančienė
  • 期刊名称:Information Technology And Control
  • 印刷版ISSN:2335-884X
  • 出版年度:2006
  • 卷号:49
  • 期号:4
  • DOI:10.5755/j01.ee.49.4.11428
  • 语种:English
  • 出版社:Kaunas University of Technology
  • 摘要:The valuation of bank activity is important to shareholders, potential investors, supervisors, government institutions and society. They are interested in safety and profitability of funds invested as well as stable and safe growth of the economy. A lot of theoretical methods of valuation exist. The internal valuation of bank usually is concentrated on shareholders’ purpose – increasing of profitability and cash flow. The external valuation is many – sided and especially concentrates on risk. In order to clarify methods, the most useful for valuation and decision making, the investigation was performed. The research showed that methods of internal valuation can be divided into two groups: methods based on cash flow and methods based on profitability measurement. Methods of external valuation can be specified for assets quality, capital adequacy, liquidity, profitability, management and other qualitative factors. As external valuation is much wider, the internal valuation should be improved by adding necessary fields of appraisal for creation of effective valuation system. As different indicators may value the same aspects of performance, the practical determination of the most important indicators is needed. Therefore the research of the most frequent methods used by internal and external appraisers was performed for Lithuania and tested on the rest of the Baltic States. The main internal and external indicators were determined. Indicators are as follows: Total debt / Total common equity; ROA; ROE; Provisions / Total loan portfolio; Non – performing loans / Share capital and reserves; Provisions / Non – performing loans; Non – performing loans / Pre – provision income; Additional expenses in income; Deposits. The selection of the significant variables was performed by using the model, based on multidimensional regression. The set of basic indicators was tested on Lithuanian and both commercial banks of the Baltic States. Three key indicators were selected for Lithuanian banks: Non – performing loans / (Share capital + reserves); Non – performing assets / Pre – provision income; Deposits. The correlation and regression analysis of stated indicators was performed. It allowed determining strong linear dependence among individual credit rating of bank and 10 main indicators. Correlation analysis of Latvian banks was not successful due to insufficient adoption of basic indicators to Latvian banks. The significance of the equation was negative and it was not possible to determine significant indicators. The correlation analysis for Estonian banks failed, but it was successful for aggregate data and showed strong linear dependence among individual credit rating of bank and main indicators. The model led to find out these significant indicators for the commercial banks of the Baltic States: ROE; Provisions / Total loan portfolio; Nonperforming loans / (Share capital + reserves); Provisions / Non – performing loans; Non-performing loans/ Pre – provision income; Deposits. The present model, based on Lithuanian commercial banks, is not universal for all the Baltic States. Modeling of bank’s financial condition, using multidimensional regression is also possible. This would lead to projection of bank’s rating by changing values of the key variables.
  • 其他摘要:The valuation of bank activity is important to shareholders, potential investors, supervisors, government institutions and society. They are interested in safety and profitability of funds invested as well as stable and safe growth of the economy. A lot of theoretical methods of valuation exist. The internal valuation of bank usually is concentrated on shareholders’ purpose – increasing of profitability and cash flow. The external valuation is many – sided and especially concentrates on risk. In order to clarify methods, the most useful for valuation and decision making, the investigation was performed. The research showed that methods of internal valuation can be divided into two groups: methods based on cash flow and methods based on profitability measurement. Methods of external valuation can be specified for assets quality, capital adequacy, liquidity, profitability, management and other qualitative factors. As external valuation is much wider, the internal valuation should be improved by adding necessary fields of appraisal for creation of effective valuation system. As different indicators may value the same aspects of performance, the practical determination of the most important indicators is needed. Therefore the research of the most frequent methods used by internal and external appraisers was performed for Lithuania and tested on the rest of the Baltic States. The main internal and external indicators were determined. Indicators are as follows: Total debt / Total common equity; ROA; ROE; Provisions / Total loan portfolio; Non – performing loans / Share capital and reserves; Provisions / Non – performing loans; Non – performing loans / Pre – provision income; Additional expenses in income; Deposits. The selection of the significant variables was performed by using the model, based on multidimensional regression. The set of basic indicators was tested on Lithuanian and both commercial banks of the Baltic States. Three key indicators were selected for Lithuanian banks: Non – performing loans / (Share capital + reserves); Non – performing assets / Pre – provision income; Deposits. The correlation and regression analysis of stated indicators was performed. It allowed determining strong linear dependence among individual credit rating of bank and 10 main indicators. Correlation analysis of Latvian banks was not successful due to insufficient adoption of basic indicators to Latvian banks. The significance of the equation was negative and it was not possible to determine significant indicators. The correlation analysis for Estonian banks failed, but it was successful for aggregate data and showed strong linear dependence among individual credit rating of bank and main indicators. The model led to find out these significant indicators for the commercial banks of the Baltic States: ROE; Provisions / Total loan portfolio; Nonperforming loans / (Share capital + reserves); Provisions / Non – performing loans; Non-performing loans/ Pre – provision income; Deposits. The present model, based on Lithuanian commercial banks, is not universal for all the Baltic States. Modeling of bank’s financial condition, using multidimensional regression is also possible. This would lead to projection of bank’s rating by changing values of the key variables.
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